Sales Software - Optimizing Direct Mail Campaigns Often companies possess huge amounts of historical data on their existing customers, and want to leverage this data to target customers more effectively for upgrades, new product launches, etc. Significant cost savings can be achieved, for example, by targeting direct mail campaigns only at customers who have a higher likelihood of purchasing additional products. Typically, the response rate on direct marketing campaigns is quite low, with a 5% response rate being quite good. By "training" the neural network on demographic data taken from those that respond, it may be possible to identify characteristics that would produce a higher response rate. If a neural network is used to analyze the demographic characteristics and a 7% response rate is achieved, then the cost of the campaign can be reduced while maintaining the same desired level of positive response from prospects. Neural networks can deliver this increased efficiency, since they have the ability to detect patterns and relationships in data that indicate a higher likelihood to upgrade or purchase new software. Unlike traditional methods, neural networks can produce accurate results even with incomplete or random data sets. Typical inputs to the neural network for direct mail optimization are: - number of products previously purchased
- industry
- position / title
- value of products purchased
- time between product launch and purchase
All of these variables can influence whether a customer is an appropriate target for a marketing campaign. NeuroXL Classifier will do the work of classifying such data and designating high-value targets for your marketing campaigns. NeuroXL Classifier Sales Software NeuroXL Classifier is an add-in to Microsoft Excel that harnesses the power of neural networks for classification of sales and other data. There is no need for the analyst to learn about neural networks in order to use the software, and the interface is extremely easy to use. To make a classification, the analyst simply specifies the input and output data, sets a few parameters, and NeuroXL Classifier does the rest! The end result is fully classified data along with graphs illustrating the properties of each group. See this example for more information. About Neural Networks Neural networks, loosely modeled after the human brain, are highly interconnected networks of independent processors that, by changing their connections (known as training), learn the solution to a problem. These networks do not require complex models to reach a solution since they learn by example. By implementing NeuroXL Classifier, your organization is provided with a powerful neural network tool that increases profits by making your direct mail and other sales and marketing campaigns more efficient and effective. More information For more information on NeuroXL Classifier, please visit our home page. Useful Links | 
